{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\" style=\"margin-top: 1em;\"><ul class=\"toc-item\"></ul></div>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# RNN in TensorFlow Keras - TimeSeries Data <a class=\"tocSkip\">"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NumPy:1.13.1\n",
      "Pandas:0.21.0\n",
      "sklearn:0.19.1\n",
      "Matplotlib:2.1.0\n",
      "TensorFlow:1.4.1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Keras:2.0.9\n"
     ]
    }
   ],
   "source": [
    "import math\n",
    "import os\n",
    "\n",
    "import numpy as np\n",
    "np.random.seed(123)\n",
    "print(\"NumPy:{}\".format(np.__version__))\n",
    "\n",
    "import pandas as pd\n",
    "print(\"Pandas:{}\".format(pd.__version__))\n",
    "\n",
    "import sklearn as sk\n",
    "from sklearn import preprocessing as skpp\n",
    "print(\"sklearn:{}\".format(sk.__version__))\n",
    "\n",
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "mpl.rcParams.update({'font.size': 20,\n",
    "                     'figure.figsize': [15,10] \n",
    "                    }\n",
    "                   )\n",
    "print(\"Matplotlib:{}\".format(mpl.__version__))\n",
    "\n",
    "import tensorflow as tf\n",
    "tf.set_random_seed(123)\n",
    "print(\"TensorFlow:{}\".format(tf.__version__))\n",
    "\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense\n",
    "from keras.layers import LSTM, SimpleRNN, GRU\n",
    "from keras.losses import mean_squared_error as k_mse\n",
    "from keras.backend import sqrt as k_sqrt\n",
    "import keras.backend as K\n",
    "\n",
    "import keras\n",
    "print(\"Keras:{}\".format(keras.__version__))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATASETSLIB_HOME = '../datasetslib'\n",
    "import sys\n",
    "if not DATASETSLIB_HOME in sys.path:\n",
    "    sys.path.append(DATASETSLIB_HOME)\n",
    "%reload_ext autoreload\n",
    "%autoreload 2\n",
    "import datasetslib\n",
    "\n",
    "from datasetslib import util as dsu\n",
    "datasetslib.datasets_root = os.path.join(os.path.expanduser('~'),'datasets')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Read and pre-process the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "filepath = os.path.join(datasetslib.datasets_root,\n",
    "                        'ts-data',\n",
    "                        'international-airline-passengers-cleaned.csv'\n",
    "                       ) \n",
    "dataframe = pd.read_csv(filepath,\n",
    "                        usecols=[1],\n",
    "                        header=0)\n",
    "dataset = dataframe.values\n",
    "dataset = dataset.astype(np.float32)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# normalize the dataset\n",
    "scaler = skpp.MinMaxScaler(feature_range=(0, 1))\n",
    "normalized_dataset = scaler.fit_transform(dataset)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# split into train and test sets\n",
    "train,test=dsu.train_test_split(normalized_dataset,train_size=0.67)\n",
    "n_x=1\n",
    "X_train, Y_train, X_test, Y_test = dsu.mvts_to_xy(train,test,n_x=n_x,n_y=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Keras SimpleRNN for TimeSeries Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "tf.reset_default_graph()\n",
    "keras.backend.clear_session()\n",
    "\n",
    "# reshape input to be [samples, time steps, features]\n",
    "X_train = X_train.reshape(X_train.shape[0], X_train.shape[1],1)\n",
    "X_test = X_test.reshape(X_test.shape[0], X_train.shape[1], 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "simple_rnn_1 (SimpleRNN)     (None, 4)                 24        \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1)                 5         \n",
      "=================================================================\n",
      "Total params: 29\n",
      "Trainable params: 29\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "Epoch 1/20\n",
      "95/95 [==============================] - 1s 7ms/step - loss: 0.0161\n",
      "Epoch 2/20\n",
      "95/95 [==============================] - 0s 2ms/step - loss: 0.0074\n",
      "Epoch 3/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0063\n",
      "Epoch 4/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0051\n",
      "Epoch 5/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0043\n",
      "Epoch 6/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0036\n",
      "Epoch 7/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0031\n",
      "Epoch 8/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0027\n",
      "Epoch 9/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0024\n",
      "Epoch 10/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0023\n",
      "Epoch 11/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0022\n",
      "Epoch 12/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0021\n",
      "Epoch 13/20\n",
      "95/95 [==============================] - ETA: 0s - loss: 0.001 - 0s 3ms/step - loss: 0.0021\n",
      "Epoch 14/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0021\n",
      "Epoch 15/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0020\n",
      "Epoch 16/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0020\n",
      "Epoch 17/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0020\n",
      "Epoch 18/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0020\n",
      "Epoch 19/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0020\n",
      "Epoch 20/20\n",
      "95/95 [==============================] - 0s 3ms/step - loss: 0.0020\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fa39c5d5c18>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# create and fit the SimpleRNN model\n",
    "model = Sequential()\n",
    "model.add(SimpleRNN(units=4, input_shape=(X_train.shape[1], X_train.shape[2])))\n",
    "model.add(Dense(1))\n",
    "model.compile(loss='mean_squared_error', optimizer='adam')\n",
    "model.summary()\n",
    "model.fit(X_train, Y_train, epochs=20, batch_size=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train Score: 23.27 RMSE\n",
      "Test Score: 54.13 RMSE\n"
     ]
    }
   ],
   "source": [
    "# make predictions\n",
    "y_train_pred = model.predict(X_train)\n",
    "y_test_pred = model.predict(X_test)\n",
    "\n",
    "# invert predictions\n",
    "y_train_pred = scaler.inverse_transform(y_train_pred)\n",
    "y_test_pred = scaler.inverse_transform(y_test_pred)\n",
    "\n",
    "#invert originals\n",
    "y_train_orig = scaler.inverse_transform(Y_train)\n",
    "y_test_orig = scaler.inverse_transform(Y_test)\n",
    "\n",
    "# calculate root mean squared error\n",
    "trainScore = k_sqrt(k_mse(y_train_orig[:,0],\n",
    "                          y_train_pred[:,0])\n",
    "                   ).eval(session=K.get_session())\n",
    "print('Train Score: {0:.2f} RMSE'.format(trainScore))\n",
    "testScore = k_sqrt(k_mse(y_test_orig[:,0],\n",
    "                         y_test_pred[:,0])\n",
    "                  ).eval(session=K.get_session())\n",
    "print('Test Score: {0:.2f} RMSE'.format(testScore))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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jjmHkyJGkpKTw5Zdf8sYbb9DY2Mj8+fNxOrUnkoiIiIhEr6pFgyCArJQkvv/dbF7fsI/b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CGEKBQjs/OprMxyRXYbXQ6jcyfH79rmVeVXJBZnJhyzzmzOJjuGrrOMFqCxqoSx2YgxcsPpApd3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\nS1aeWbndm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wUjYA+MGIHtKv7uO2cIRBb521ddxoGGCq5qq+bLvxhM29c3Phel3uLrGg2N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nNSWl5bQ55+fQYVCYi/PVO/a1iB6KIV1a0bFlHs+/v3b/Df3HhylYDmHOzd9PW0RutnH1mB4h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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa39c1cd240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# shift train predictions for plotting\n",
    "trainPredictPlot = np.empty_like(normalized_dataset)\n",
    "trainPredictPlot[:, :] = np.nan\n",
    "trainPredictPlot[n_x:len(y_train_pred)+n_x, :] = y_train_pred\n",
    "# shift test predictions for plotting\n",
    "testPredictPlot = np.empty_like(normalized_dataset)\n",
    "testPredictPlot[:, :] = np.nan\n",
    "testPredictPlot[len(y_train_pred)+(n_x*2):len(normalized_dataset),:]=y_test_pred\n",
    "# plot baseline and predictions\n",
    "plt.plot(scaler.inverse_transform(normalized_dataset),label='Original Data')\n",
    "plt.plot(trainPredictPlot,label='y_train_pred')\n",
    "plt.plot(testPredictPlot,label='y_test_pred')\n",
    "plt.legend()\n",
    "plt.xlabel('Timesteps')\n",
    "plt.ylabel('Total Passengers')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Keras LSTM for TimeSeries Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "lstm_1 (LSTM)                (None, 4)                 96        \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1)                 5         \n",
      "=================================================================\n",
      "Total params: 101\n",
      "Trainable params: 101\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "Epoch 1/20\n",
      "95/95 [==============================] - 1s 7ms/step - loss: 0.0551\n",
      "Epoch 2/20\n",
      "95/95 [==============================] - 1s 8ms/step - loss: 0.0278\n",
      "Epoch 3/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0205\n",
      "Epoch 4/20\n",
      "95/95 [==============================] - 1s 6ms/step - loss: 0.0188\n",
      "Epoch 5/20\n",
      "95/95 [==============================] - 1s 5ms/step - loss: 0.0179\n",
      "Epoch 6/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0168\n",
      "Epoch 7/20\n",
      "95/95 [==============================] - 1s 5ms/step - loss: 0.0158\n",
      "Epoch 8/20\n",
      "95/95 [==============================] - 1s 6ms/step - loss: 0.0150\n",
      "Epoch 9/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0139\n",
      "Epoch 10/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0130 ETA: 0s - loss: \n",
      "Epoch 11/20\n",
      "95/95 [==============================] - 1s 6ms/step - loss: 0.0120\n",
      "Epoch 12/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0109\n",
      "Epoch 13/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0100\n",
      "Epoch 14/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0090\n",
      "Epoch 15/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0080\n",
      "Epoch 16/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0071\n",
      "Epoch 17/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0064\n",
      "Epoch 18/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0055\n",
      "Epoch 19/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0048\n",
      "Epoch 20/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0041\n",
      "Train Score: 32.21 RMSE\n",
      "Test Score: 84.67 RMSE\n"
     ]
    },
    {
     "data": {
      "image/png": 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G5syZg9OpPZFEREREJHDlzRYIAkiNj+H7x2awaONebj/veKKiAt+u73ChyqZEpBtuuIHK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\nXqOzuVfGaFeacDY7MSBoyezY7Gnc2fzs45/lx/M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upoKN/O5KGu0udjYfmo5itymunAg0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BHj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\ndU42zczMzMzMrOr+P2ADHemibVO6AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa3502ffef0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tf.reset_default_graph()\n",
    "keras.backend.clear_session()\n",
    "\n",
    "# reshape input to be [samples, time steps, features]\n",
    "X_train = X_train.reshape(X_train.shape[0], X_train.shape[1],1)\n",
    "X_test = X_test.reshape(X_test.shape[0], X_train.shape[1], 1)\n",
    "\n",
    "# create and fit the LSTM model\n",
    "model = Sequential()\n",
    "model.add(LSTM(units=4, input_shape=(X_train.shape[1], X_train.shape[2])))\n",
    "model.add(Dense(1))\n",
    "model.compile(loss='mean_squared_error', optimizer='adam')\n",
    "model.summary()\n",
    "model.fit(X_train, Y_train, epochs=20, batch_size=1)\n",
    "\n",
    "# make predictions\n",
    "y_train_pred = model.predict(X_train)\n",
    "y_test_pred = model.predict(X_test)\n",
    "\n",
    "# invert predictions\n",
    "y_train_pred = scaler.inverse_transform(y_train_pred)\n",
    "y_test_pred = scaler.inverse_transform(y_test_pred)\n",
    "\n",
    "# invert originals\n",
    "y_train_orig = scaler.inverse_transform(Y_train)\n",
    "y_test_orig = scaler.inverse_transform(Y_test)\n",
    "\n",
    "# calculate root mean squared error\n",
    "trainScore = k_sqrt(k_mse(y_train_orig[:,0],\n",
    "                          y_train_pred[:,0])\n",
    "                   ).eval(session=K.get_session())\n",
    "print('Train Score: {0:.2f} RMSE'.format(trainScore))\n",
    "testScore = k_sqrt(k_mse(y_test_orig[:,0],\n",
    "                         y_test_pred[:,0])\n",
    "                  ).eval(session=K.get_session())\n",
    "print('Test Score: {0:.2f} RMSE'.format(testScore))\n",
    "\n",
    "# shift train predictions for plotting\n",
    "trainPredictPlot = np.empty_like(normalized_dataset)\n",
    "trainPredictPlot[:, :] = np.nan\n",
    "trainPredictPlot[n_x:len(y_train_pred)+n_x, :] = y_train_pred\n",
    "\n",
    "# shift test predictions for plotting\n",
    "testPredictPlot = np.empty_like(normalized_dataset)\n",
    "testPredictPlot[:, :] = np.nan\n",
    "testPredictPlot[len(y_train_pred)+(n_x*2):len(normalized_dataset), :] = y_test_pred\n",
    "\n",
    "# plot baseline and predictions\n",
    "plt.plot(scaler.inverse_transform(normalized_dataset),label='Original Data')\n",
    "plt.plot(trainPredictPlot,label='y_train_pred')\n",
    "plt.plot(testPredictPlot,label='y_test_pred')\n",
    "plt.legend()\n",
    "plt.xlabel('Timesteps')\n",
    "plt.ylabel('Total Passengers')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Keras GRU for TimeSeries Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "gru_1 (GRU)                  (None, 4)                 72        \n",
      "_________________________________________________________________\n",
      "dense_1 (Dense)              (None, 1)                 5         \n",
      "=================================================================\n",
      "Total params: 77\n",
      "Trainable params: 77\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "Epoch 1/20\n",
      "95/95 [==============================] - 1s 7ms/step - loss: 0.0538\n",
      "Epoch 2/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0274\n",
      "Epoch 3/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0198\n",
      "Epoch 4/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0178\n",
      "Epoch 5/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0168\n",
      "Epoch 6/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0159\n",
      "Epoch 7/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0151\n",
      "Epoch 8/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0142\n",
      "Epoch 9/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0135\n",
      "Epoch 10/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0126\n",
      "Epoch 11/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0118\n",
      "Epoch 12/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0110\n",
      "Epoch 13/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0102\n",
      "Epoch 14/20\n",
      "95/95 [==============================] - 0s 5ms/step - loss: 0.0093\n",
      "Epoch 15/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0083\n",
      "Epoch 16/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0074\n",
      "Epoch 17/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0065\n",
      "Epoch 18/20\n",
      "95/95 [==============================] - 1s 5ms/step - loss: 0.0056\n",
      "Epoch 19/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0049\n",
      "Epoch 20/20\n",
      "95/95 [==============================] - 0s 4ms/step - loss: 0.0041\n",
      "Train Score: 31.50 RMSE\n",
      "Test Score: 92.76 RMSE\n"
     ]
    },
    {
     "data": {
      "image/png": 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0NjYye/ZsnE7tiSQiIiIi/itrtkAQQGZyAt8/IYuFG3ZzxwUnERfn/3Z93YUqmxKTbrzx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u+rpyi5aNnOmqxwVHB64DTOQeeUcwc6596vOdG1JdcSZYniqqKrsFlDLItfRt4qHWkl2BRCCCHE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\nOew8zIaMDeY1jIqg8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/pnL6NtOTDv5kBBxYHscHXcJuhvhd7GGa9t6PKQP9cok1A17zMe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\ntnvmrGb7MWh4DbZ91OgoGlCaaae6YwCtt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vuP+oeAl5aouZo3rx2wZk6aphEf6smB7PL2\nF8Ytg5oi1fSn2fa0YnQdLpncJqtZeEzNbp37U9XYSQghhBiGJNgUQohe0nWd5zakMSbAnSUtcxLL\nc06POVn4II4mA1F+bhzPbz9ShNHzVTBReHRQ9ppbVkujWSeqbWbTYoGcPRA6vdP6AE9nbpsfjZOp\nTVBpdIBpq2DU6H7tZXK4F5pG+3ObLaW0qetUx1Q7s1h0TpXXEupzOth0MBpY5J3PMUskVQ1mXrhx\nOl6uDjDlBvjBm6oB0u3fQ9jAjtpIDPfmWF4ltQ1txrGMXarOxbYJvvdlleHhZCLGv00Z75FPAA3G\nLx/QPQohhBD9IcGmEEL00obkQo6equD2+dEYDJoK3j6+A8wNcOWLYFKNeGID3TnRKdhs7giaNjil\ntC1jT9plNktSob580OcWejo7EOPvzr62HWlBBZvmBkj+yu7vWVhVT6NZb5fZxGLBueQ4kRPP4e3b\nZrZv7hR3Max8CTyDOz/MzhLDfTBbdA61LaV1clddZI+uac1+78sqY3K4l/q91uLIJxAxq0/nZ4UQ\nQojBIsGmEEL00nMbUgnydObyxFD1wtZ/QvomNebEb0zruthADzJKaqhrbJO58o5QZyAHqUlQRoka\ne9LuzGZ2kvoe1jmzOdASwrzZl1WG3nb8S+h08AiBw6vt/n45zTM2Q72dT79Ylg6N1QSNndY6kmUo\ntLx3u0wvqOC78hTkJFHbYOZYXmX7fRadgIIjap0QQggxjEmwKYQQvbA3s5TtaSXcOne0ataSuxfW\n/VGVM065sd3a2EAPdB1SCqraPyR6AWRsAXMTAy2juAZHk4EgzzbBVs5ucHQHv9gBf/+OEiO8Ka5u\nILt59iWg5idOuAxSvoX6yq5v7oOWGZuh3m2C7fzD6nvgRLu+V2/5ezgR6u3SOdMbewEYHeHIJxzK\nLcds0UkIaxNstpTYjr908DYrhBBC9IEEm0II0QvPbUjF09nEtedGtI45wS1ANdDp0PEzNlCdsUu2\ndm6zvgJO7Rvw/aYXVRM5yrV9CWbObnW21M4dVm0xpTlDt9dqKW293Utpc5szmyFtM5t5h0AzgP/Q\njwJJjPDuHGw6e0HMYjjyCfszS1vXtTryCYTNAK/QQdypEEII0XsSbAohhI1SC6v4+kg+N86KxN3J\nBNv+A8WpcOXz4Dqq0/pIXzccjBrJ+R0ym1Hz1fdBGIGSWdJh7EljnepiOsjnNVuMC/LAyWToXDoa\nfi64B9m9K21OWS0eziY8nB1Ov5h/CEbFtOvEO1SmhHuTU1ZLQWVd+wvjl0N5FsUpOwj1diHAozlY\nLjkJeQekhFYIIcSIIMGmEELY6IUNaTgYDaya3dyVNe17CElUmUorHIwGYvytNAly94eAiQN+blPX\nddKLq9s3B8o/BJbGIQs2HYwGJoV6sT+7Q7BpMKiy0BPfqIyxnbSdsdkq//CQl9C26PLc5riLwGAi\nJOfr9uc1j65R36ULrRBCiBFAgk0hhLBBfkUdH+/N4appYfh7OKkMYXYSRM7p9r6xgR6dx5+AClAz\nt6vnDJCCynrqGi3tx54MYXOgFonh3hzKKafR3GHW6ITLoKlWBZx2klNW1z7YrK+C0pMQGG+39+iP\n+FAvTAatcymt6ygaIuYxr3EriWFt5mge+QSCE8EncnA3KoQQQvSBBJtCCGGDlzefpMli4fb50eqF\n3D3qjGHk7G7viw1wJ7u0lur6Ds2ARs+HpjrI3jVAO1bnNaHD2JOc3eARDJ4hA/a+PUmM8Ka+ycKx\nUx2C8MjZ4Opn11LanNKadjM2KWiebxo0PIJNZwcjccEenYNNIMXvPKIM+cxyP6VeKMtUv35SQiuE\nEGKEkGBTCCFs8NmBUyyOCzwduGVsUd8jZnV7X2zzDMdOHWmj5qgmNQNYSptR0jJjs01mMydpyEpo\nW7SWjmaVtr9gMKpS2uSvoLHWyp29U1nXSEVdU/sZm/kH1fdhUkYL6udxIFt1nW1rHdMx6xrjitep\nF45+qr5LsCmEEGKEkGBTCCF6UF3fRE5ZLYnhbcoZM7ZBwASrjYHaig1UwWanjrTOXqoj7EAGm8XV\nmAza6TLSmhIoSRvyYDPU2wU/d6fOHWkB4i6BxmrI2Nrv9zlVrkqU2webh8HJE7zC+/18e0kM96Gq\nvonUwvb/ILEtT+OgwyQcjq8BXYcja1T5r2/MEO1UCCGE6B0JNoUQogdphaocNcZfjTLB3ARZO3rM\nagJEjHLFyWToHGwCjFminlOcas/ttkovriHMxwWTsfmP+tw96vsQntcE0DSNxHAvq6WjRM5WMyZT\n1/X7fU7P2OwQbAZO7DSmZii1/CNG25+HxaJzIKucjMDzofiE+nlkbZesphBCiBFFgk0hhOhBSqEK\nFMcENAebeQegoarH85oARoNGjL975/EnANNvUYHV1n/ac7utMotriGh7XjN7N6CpBjNDLDHcm7TC\nasprGttfcHSFiJmQur7f75FT1iHY1PXmYHN4nNdsEe3njoezqV2wmVpYRWV9E9r4SwENPrtfXZBg\nUwghxAgiwaYQQvQgpaAKo0Frc16zucTThmAT1GzJTuNPADyCIPE62Pc2VObZabdKy9iTdp1oc3aD\nfxw4e9r1vfoiMdwHoPMIFICYxVBwuG8/k4pTkLUTUMGmg1EjwMNJXSvLhPqKYXVeE8Bg0EgI8243\n/qQl8JwQO0b9PivLVL92/uOGaptCCCFEr0mwKYQQPUgtqCbS1xVHU/MfmZnbwGe0zR1dxwa6k1te\nR2VdY+eLs+8DSxNsf8aOO4bSmkYq65pOB8i6PiyaA7WYHO6FpmG9lDZ6kfqe9r1tD6srhz1vwGuX\nwt/Hw0vnQ+YOcstqCfJyxmBoLpnNP6y+D7PMJqhM7/H8SmobzID6uXg4mYj2cz89U1NmawohhBhh\nJNgUQogepBRWMablvKbFojKbPczXbCs2oKVJkJVSWt8YmHA57HoZaq0EXn2UUdw89mRUc2azLANq\niiF0qt3eoz88nR2I8Xe3HmwGTQZX355LaXP3wXs3wt/Gwpp7oSwL5v8C3ALguz+QW1pDiFeH85oA\nAePt90HsJDHcG7NF52BOOaCCzcnhXipQnnQVjLsYpt44xLsUQgghesc01BsQQpyBynOgtqTz675j\nwMGl8+vDWKPZQnpRNedPCFQvFB1Xny2y5+ZALVo60p7Ir2RapE/nBXPvh8MfQdJLMO8Be2ybjGI1\n9iTKrznYzE5S34e4OVBbk0O92JJa1PmCwaCym2nrVUbWWjMfi1kFmg2VMG0VTL5aZW01Ddz8Ye0v\nCHPYhjZ2yel78g+pjLST+4B9pr5KjDg9DmZSqBfH8iq5c0HzTFc3X7j27SHcnRBCCNE3EmwKIeyr\nIhf+OQXM9Z2vBU2G29aDceT80ZNRXEOTRT+d2WyZr2njeU2AMB8XXByMHMuzcm4TIDgBYs6D7c/C\nzLvtEpCnF1ejaRDm0xxs5uwBk7Ma1zJMxAV78NHeHEqqGxjl5tj+YswiOPQBFByxfsYydT2UZ8LK\nVyD+yvbXpt2EvvWf3FL6Bl97XXL69fzDEDT8SmgB/NydCPNxYV9WGVMi1MzNlnOtQgghxEglZbRC\nCPva+6YKNC9/Fn7w5umvxY+oLq573xjqHfZKSoEqfW3tRJuxDTyCVYbMRgaDxtRIbzZKMi6oAAAg\nAElEQVSnWMnitZj7U6guhH1v9We7UFUIKd/hlv4dK9wP43zyW0j+Ss3zDE4Eo0P/nm9HcUGqUdGx\nvIrOF1vObXY1AmX3K+Dqp+ZydmRyouzcnzPJkM65dZvVaw01UJI6LM9rtkgMV02CWhoFJYZ7D/GO\nhBBCiP4ZOekFIcTwZzHDntcheqHqstpW3CWQ8h2s/xPErxgWHVFtkVqogs2YAHdV0pmxVWU1ezmn\n8fzxgTz66RFOFlUz2s+t84KouRA2A7b8E6ausi37q+tQmq4aFmVsVd+LUwC4rWVN2+rLuT/t1Z4H\n2vjg5mDzVCWzY/zaX/QKBb9xKticfV/7axWn4PhamH0vmDpkRJudCLwYb8tfmZr6HzCvgsKjoFuG\nXSfathLDvfnswCm+PpJHqLcL/i1ddIUQQogRSjKbQgj7SfkOyrPUGbqONA0ueExl7zY/Nehbs6qu\nXGUqu5FaUEWwlzPuTiYV2FXmQoTt5zVbLGk+8/nNkS7GeWiaCgbLMuDIatseuvFv8M9EWH0XHP0U\nfMfCkt/Dqs+50fAX/jPmBbhtXfPXelj4m17veyD5ezjh5+5oPbMJagRKxlZorGv/+t43QTfD1Ju6\nfHZuRQNPNl2Na0Ua7H+nTSfa4RtsTmk+t7krvbT1DKcQQggxkg15sKlpmq+maT/SNO1jTdNSNE2r\n1TStXNO0zZqm3appmtU9apo2W9O0LzRNK2m+54Cmafdrmmbs5r0u0TTt++bnV2matkPTtK7/tiKE\n6J3dr6rmLOMutn49dBpM/gFs+4+aGziUdB3eXwWvXAgnvulyWUphFTGt5zVb5mva3om2RZiPKxOC\nPfn6cH7Xi2IvUtm8zU+r/XWnqV6NS4leCHdtg1+ehOvehbn3Uxl0LptqIjCGT1c/89Bpqgutafhl\nyuKCPLs+yxqzCJrqVMa2RUv2fPQC8I1B7+LnlFNWy1eW6VhCpsL3f1EzRh3dwTvK/h/CTiaGeGFq\nHtMyRUpohRBCnAGGPNgErgL+C5wL7ACeBj4E4oEXgf9pWvt6NU3TLgM2AvOBj4F/A47AU8C71t5E\n07R7gU+bn/tm83uGAK9qmvaE3T+VEGebilxI/hISr++ytBGA836rsnjf/WHw9mbN/ndViaaTJ3xy\nD1QXd1qi6zqpBVVtzmtuBRcf8I/r01sunRjI7sxSiqqsNE8C1YV17v2Qf1BlibtzfC3UlqoS08AJ\n6t5mLZ1oW8eeDGNxQR4cz6vEbLESNEbOAYOD6krbInUdlGey0/cy5v11HXe9ucfqc3PKahnl5oRh\nye+gIltlQwPa/5yGG2cHY2tpsZzXFEIIcSYYDv+vmwwsB8J0Xb9e1/Xf6Lp+CxAHZAErgNZWg5qm\neaICRTOwUNf1W3Vd/wWQCGwDVmqadk3bN9A0LQp4AigBpuu6fo+u6z8FJgOpwAOapvW+Lk4IcVpr\naeMPu1/nFQaz7oWD70P27sHZW0dVBfDlryF8Jqz6XAVtn/64UzbxVHkd1Q1mdV4TIHMrRMzuc8By\n/oRAdB3WHS3oelH8SnAPgu3/6f5he98Ez9DTjXTaaA02fa2cDR1m4oI9qW+ykN48F7QdJ3eImNna\nJEjXdQo3PE+p5s31m/0oq27k6yN5FFTUdbo1t6yWEG9nlfkdvQAsTcO6hLbFtEgfHI0G4kO9hnor\nQgghRL8NebCp6/o6Xdc/1XXd0uH1POC55v9c2ObSSsAfeFfX9aQ26+uAh5v/864Ob3ML4AT8W9f1\n9Db3lAJ/bv7PO/v3SYQ4i7VtDOQb0/P6ufeDWwB89WDP5aIDYe0vobEGlv8LgierTrnHPlMBXBst\nzYHG+LurpjQlab0aedLRhGBPQr1d+Lqrc5ugssLn/EgFWAVHra+pyIXU7yDhWjB0PjnQErhF+o6M\nzCaoJkFWRS+EvIMcPpHCPc99gU/Wd3xuXMQT10zno7tnY9HhswOnOt2WU1pLqHfzCJnzfgdoqpR4\nmPvJeWN5746ZODt0eSJECCGEGDGGPNjsQWPz96Y2ry1u/v6llfUbgRpgtqZpbQ8ndXfP2g5rhBC9\n1V1jIGucPGDxQ5C1HY6uGdCtdXLsczj8MSz4JfjHqtdm3QtR81S2s+Rk69J2Y08yW85r9r0IQtM0\nzp8QyKYTRdQ0NHW9cNotaibm9mesX9//juqs2rHjb7PM4hr83J1wcxr+DcfHBLhjNGjdNwkCXn79\nFeIL1mDSLFx9+8NclhjK2EAPJgR7smZ/brtbdF1vzmw2B5th0+DeJEiw/vMaTnzcHJkSIfM1hRBC\nnBmGbbCpaZoJaKnHaxskjmv+ntzxHl3Xm4CTqJEu0TbecwqoBsI0TRv+aQAhhpFGs4XNJ4oo3PA8\nDU6+fM8M1h8rYENyIXWN5u5vnnIjBEyEb34L5sbu19pLXTl8/oCatTjn/tOvGwxqLqhmhI/vALMK\nBFMKqvB0NuHn7qjOazq4QVBCv7awdEIg9U0WNp3oZuammy8kXAP734PqDut0Hfa+pc4zdpFFTi+u\nJmoEZDVBnVOM9nPjaFeZzeAEGhy8mM0+bnXbBNELcQwY03p5eWII+7LKyGwuHQYor22kusF8OrMJ\n4DfGtnEyQgghhLCbYRtsAn9BNfP5Qtf1r9q83nKQpbyL+1peb9tdwdZ7rB6S0TTtdk3TkjRNSyos\nLOx+10KcRd5PyuaBl9bik72Ol6pns+qN/dz86i5uenknz6xP6f5mg1FlN0vT4cTXg7JfvvktVOWr\n8lmjQ/tr3uFw8ZOQtUONZqmvxDVrA4+4foT26iWqTDji3H4HLDNGj8LT2dR9V1qAmXeDuR6SXm7/\neuZ2KElVjZi6kFFcMyLOa7aIC/bsOrNpMHLUZRqXGbfiVJXTKXt+aUIIAGv257S+llNWC9A+2BRC\nCCHEoBuWwaamaT8GHgCOATcO8XbQdf0FXden67o+3d/ff6i3I8SwsTG5kFvdNmPSLCy49uesvmcO\nq++Zw8zoUXy4JweLtQ6jbY29ANwDVaZuoJ3cpEazzLqn67N7k6+C+BXw/Z/hL5E8VPIQK2r+Bw1V\nMONHcMHj/d6Gg9HA4rgA1h3Lp8ls6Xqh/zgYswR2/leNOWmx7001wmPCZVZvq2s0k1dRN2Iym6DO\nbWaX1lJR1znDres6X9SMx4TF6lidUG8XZkT5tCulzS1TDYNCJNgUQgghhtSwqylqHlHyD+AIcJ6u\n6yUdlnSbhWzzelmHe/yar3Web9Bz5lMI0YHZorM9tYDHHdZD5EImTExsvXbtORH85N19bE8rZvYY\nv64fYjSpctGt/1YdYt0DBmaz5dnw8Z3gMxoWPtj92oufBKMjda4h3LbBgcVLLubmxZPtup2lE4NY\nvS+X3RmlnBvt2/XCmXfDm1fCoQ/V+cz6Kjj0McRficXBjZ1pxRw91T4jWFrdAEDECAo2xwerJkHH\n8yqZETWq3bWM4hrWVMXxa2cNbcoNVsfqLE8I4ZFPDnMsr4K4IE9ySlVJbaiPBJtCCCHEUBpWmU1N\n0+4H/gUcAhY1d6Tt6Hjz91gr95uA0aiGQmk23hMMuAHZuq7XdLwuxBkt7yC8uATKc3pe28Gh7DKu\na/wYn8b8TqWNF0wMwsPJxAd7snt+UOINamTKgfd6vQebVBfB65dDfQVc/To49hCEufjAFc9xOO5e\nNlkmExkSaPctzY/1x9Fo4OsjPZTSxiwG//Gw7Rl1VvPIamis5s2Gecz9v3Vc88J2fv/pkXZf/1yX\ngsmgjajRGXFBarbksVOdS2k3pxRxCl9yr/oMFvza6v3LJgVjNGis2aeym7nldTiaDPi6dTPvVQgh\nhBADbtgEm5qm/Qp4CtiHCjS7GkS3rvn7hVauzQdcga26rredmt7dPRd1WCPE2WPf25C9C9Y91rv7\nqgrwXn09v3R4j/oxF0LcJe0uOzsYuXhyMF8eyqO6vpuuq6A6wobNaJ7TaecxKHUVKjNYng3X/U+N\nObFRSyfaGH93++4JcHcyMXuML98cyUfv7jNrGsy8C/IPsm3dag59/gyplmB+t9ed2CAP/nFNIkkP\nL2Hfb89v93Xg0aUDsu+BEuzljKeziaN5nZsEbUkpItTbhZAJc8DB2er9vu5OzBnjx5r9uei6Tk6Z\nGnuiadpAb10IIYQQ3RgWwaamaY+gGgLtRpXOdtOmkQ+AIuAaTdOmt3mGM9DyN+ZnO9zzClAP3Ktp\nWlSbe3yAlpq65xDibKLrcHwtGExqlMap/bbdd+IbeHY2wSW7+Lfr3Thd/27nZjvAimlh1DSYWXuo\nm5mSLabcAIXHIGdPLz9ENxpr4Z1rIf8wXP0631RHsy3VWhW9dSkFVTiaDIT5DEw56vkTAsksqSE5\nv6r7hZOvRnfxxWPj74lvOkxZ7FXseHAJr958DpclhuLn7oS3q2O7L1fHYXdColuapqkmQR0ym2aL\nztbUYuaM8e0xcLwsIYTs0lr2ZJa1n7EphBBCiCEz5MGmpmk3AX8AzMAm4Meapj3a4WtVy3pd1yuA\n2wAj8L2maS9qmvZXVEZ0FioYbVePp+v6SeAXwCggSdO0/2ia9hRwAIgBntR1fdtAf1YhhpWiE1B6\nEhY9qEpHv3qo+8xiYx2s/TW8tRKLqz+XN/6J8ok3quybFdMjfYj0deWD3Vk972XilWByUc1v7MHc\nCO/fDBlb4IrnKQ9fxE/e3cv97+2lvqmHkSzNUgurifZzw2gYmOzY+eNVee7Xh3sIxh1cyIq5hnjt\nJLpmYNryu/Fzd+r+nhFoQrAnx/Mq2zWVOpxbTnltI3O6O/fbbOnEQJxMBj7dn9s8Y9N6FlQIIYQQ\ng2fIg03UGUtQweP9wO+sfK1qe4Ou66uBBcBGYAVwH9AI/Ay4RrdSl6br+r+A5cBh1PzO24E8YJWu\n6z+394cSYthLbh5fO+lqWPgbSN8EyV9ZX9tQA29cDjuehXPvZOt573PEHNptEKBpGiumhrE9rYSs\nkh6OQzt7woTlcPBDlZHsj8Y6WH03JK+Fi5+ASSt5PymLmgYz+RX1fLI3t+dnoDKbYwIGrhQ1wNOZ\nxHBvvjnaw7lN4DOni6nXTZijzwPP4AHb01CKC/KgusFMdunpX//NKarIZXZMz8Gmh7MDi+MC+HR/\nLoVV9YR6j5wGSUIIIcSZasiDTV3XH9V1Xevha6GV+7bour5M13UfXddddF2fpOv6U7qud5m20HX9\nU13XF+i67qHrupuu6zN0XX9tQD+gODt99jN4YWHnr0/vB4ttmbUBl/wVBMar+ZLTbwbfMfDNI2Du\ncMayqQH+90M133HFS3DR/7HpZCUORo1zRo+y/uxmV0wJBeDjvTY0IJpyA9SXw9HP+vqJVInvMzPh\n4P9g8SMw40eYLTqvb8tgWqQPE0M8eW5jao8jWeoazWSV1gxosAmqlPZAdjkFFXXdrvsuW+P33n/C\ndOlTA7qfoRQXrJoEHW0zb3NLShFxQR74e9iWyV2eEEJxdQO6jmQ2hRBCiGFgyINNIc44eQch6SVV\nkurmf/rL0R12vwLb/j3UO4TaUsjcBrHNPbOMDnD+H6AoGfa8enqdxQyr74SUb+DSp2HSSkAFAVMj\nfHo8Gxg+ypWZ0aP4aE92941wACLngndE30ppSzPgnevgrZXqDOqNq2G+Klj4/ngBmSU13DwnijsW\nxJBWWN1jNjGtsBpdH5jmQG0tjlOjXtYf76ofGlTXN7E/qwyv8QvVPwycoWID3dE0OHZKNQmqazSz\nK72UuTaU0LZYFBeAu5P6PSlnNoUQQoihJ8GmEPa2+zUwOsGNH8P175/+uulTGH+p6vyad2ho95jy\nnRo3EtumQfO4ZRA5B9Y/rrq46jp88Qs143HJo63jTUqqGzicW2FzELBiahjpxTXszijtfqHBAInX\nQ9oGKMu07XM0NcCGv8J/zoG072HJ7+GurRCzqHXJq1vTCfJ05oKJQSyLDyJ8lAvPbUjtNvhNKVRN\newY6sxkX5EGwlzPrjnUdbCZllNJk0ZnV3TzOM4Cro4koXzeONWc2k9JLaWiyMGes7cGms4ORCyYG\nATJjUwghhBgOJNgUwp4aauDA/2DCZeDaocRU0+CSf4CzN3x0OzTVW3/GYEj+Elz9IHRq+/0tfQxq\nimDzU7D+TypDO/vHMPenrcu2pRaj69gcBCybFIyro5EPdtswczPhWkCHfe/Y9jk2Pan2Oe4iuHcX\nzL0fTKdnK57Ir2TTiSJumBmBg9GAyWjg9nnR7M0sY+fJki4fm1pQhUGD0X5utu2jjzRNY1FcAJtP\nFHXZuGhbajEORo3pUT4DupfhIC7Ig2PN4082pxSpUu2o7ku1O7prYQy3zBlN+AB1ERZCCCGE7STY\nFMKejqxW5w6n3WT9upsvXPYfKDjc+9mW9mJuUmcbYy8Ag7H9tdCpqmHQln/Axr/BlBtVeW0bm1OK\n8HAyMTnUy6a3c3MycWF8EJ8fOEVdYw/nVX0iYfQC2PcWWCzdr21qgKSXVXb2qlfBK7TTkte2peNo\nMnDtORGtr101PRxfN0ee25Da5aNTCqsIH+WKs4OxyzX2snhcANUN5i6D321pxSSEeY+4cSZ9ERfk\nSXpxNTUNTWxJKWJKhA9uTr373GMC3PntpRMwDFAXYSGEEELYToJNIexp96uq0U7knK7XxC6F6bfA\n1n9B+uZB21qrrB1QV6aCTWvO+y04uKrs7KX/6DTaZEtKETNjfDEZbf/jY+XUMCrrm/iqpzEfoBoF\nlWWo7rjdOboGqgtgxm1WL5fXNvLRnhyWJ4Tg22ZUiLODkVWzo1h/vLC1ZLOj1IIqxgzwec0Ws8f4\n4mgyWC2lraxr5FBOObNizuwS2hZxwR7oOuw4WcKh3PJendcUQgghxPAjwaYQ9lJwVAVyU2/qcvZk\nq6WPwajR8PGdUFc+OPtrkfwlGBwgepH1697h8LPDcNVrnTKfmcU1ZJbU9DoImBntS6i3C6tt6Uo7\n/lLVUGnTE92v2/US+IyGmMVWL7eMO1k1O6rTtRtnReLqaOT5DWmdrpktOmlF1cQM8HnNFq6OJmZF\n+7LeSrC5K70E81lwXrPF+CDVkfaVLemqVFuCTSGEEGJEk2BTCHvZ/ZoK4hKv63mtoxtc+V+oyIW1\nvx74vbWV/BVEzVGzLbvi7GU1YN6SquYe9jYIMBg0lowPYHtaCQ1NPZTHOrjA3J/ByY2qWZA1+Ych\ncyvMuFU1FuqgZdzJjCgf4q2U+3q7OnLtORGs2Z9LdqmaAVrXaOaLg6e4440kGposjB2kYBPgvPEB\npBfXkNbcmKjFttRiHI0Gpkae+ec1AcJ8XHBzNLIxuRB3JxMJYbaVagshhBBieJJgUwh7aKyD/e80\nZ+VsDMTCpsO8B2D/25C5Y2D316IkDYqOQ+xFfbp9c0oRQZ7OxPj3vnHOrBhfahvNHMgu63nx9FvA\nMxTW/VF1xe1o53/B5Ky611qx/pgad7Jq9ugu3+LWuaPRgD99fpRffXCAGX/6lrvf2sOB7HLumB/N\nZYmdz4AOlEXj1AiUjqW029KKSYzwHpSzo8OBwaAxLsgDUNnw3pRqCyGEEGL4kf8nF8Iejq5R5yC7\nagzUlTk/UUHToQ8GZl8dJX+lvscu7fWtFovO1pQi5ozxQ+upTNiKc0f7omkqW9cjB2dY8EvI3nV6\nzy3qylXH3/iVnTv+Nnt1azrBXs4snRjY5VuEeLtwWWIoaw/l8dmBXJZOCOLNW89l22/O4zfLxuNo\nGrw/HsNHuTI2wL3dvM3ymkYO51acNSW0LeKCVcZ97piz63MLIYQQZyIJNoWwh92vqvODUfN7d5+T\nO4xZAkfW9Nx91R6SvwS/cTAqute3HjlVQWlNI3PH9i0I8HFzJC7Ik21pNgSboLKWPqNV1962P5v9\n70JjtSqhtWJPZimbU4q4YWYkDj1kxn57yQReXjWdpIfP58mrE5g71g/jEHUxXRwXwI60EirrGgHY\ncVKNmDlbmgO1aOlyPHes/xDvRAghhBD9JcGmEP1VdAIytqisppXzgz2aeAVU5UHWdvvvrY2K8hL0\n9C1dd6HtwZaU5vOaMX1v2jIr2pfdGaVdzpRsx+gAix6E/INqpAyoktpdL0LotPYzQps1mS089PEh\ngjyduclKY6COvFwdWBwXiIvj0JepLooLoMmis/mE+jlvTyvByWRgSoT3EO9scK2YFsYn98xhzCCe\nmRVCCCHEwJBgU4j+2v0qGExdnh/sUewFYHSCw6vtuq2OPnjvNTRLI+axF/b63rzyOl7flkFckAcB\nns593sOsGF/qmyzszbTh3CZA/ArwHw/r/6Tmg57cCEXJMONHVpe/siWdo6cqeHT5BNx7OZ9xqE2L\n9MHD2dR6bnNbWjHTIn1wMg19IDyYHIwGEsLPrgBbCCGEOFNJsClEfzTVw763YdwycA/o2zOcPGDs\n+erc50CV0ubsZuGplyjT3dja0LsS2pLqBm54aQfltY38bWVCv7ZxzuhRtp/bBDV6ZfFDUJwCB96F\nXf8FFx+YeGWnpTlltTz1bTLnxQVwwcSgfu1zKDgYDSyI9Wf98UJKqhs4eursO68phBBCiDPLyPqn\nfzFy7HhBBU8deUfAxU+q8RZnguSvoLZEzdbsj4lXwLHP1JzOyFn22RtATQl89wf03a/irnvxs8a7\n8Nybx7xxwTbdXlXfxM2v7CSzpIbXbzmHSf0cReHl4sDEEHVu86e23hR3CYRMUWc3qwpg1j2qgVAH\nj645jEXXeXT5xD41MBoOFscF8NmBU7y0Wc3/PNvOawohhBDizCKZTWF/mTtg7S9VYKBbTn9ZmmDf\nW/Dto0O9Q/s59AG4+UP0wv49p6WU9oidSmktFjX381/TYM/r5IxbxeL6J8j0m8+Xh/Nam9B0p67R\nzO2vJ3Eot4JnrpvKTDtl2WZF+7Ivs4y6RhvObYKa97n4Eag8pX4fTb+l05KvD+fxzZF87l8SS/go\nV7vscygsiPVH0+DFTSdxcTAyOUzKSYUQQggxckmwKeyrqR7W3AdeYXDbOrj5i9Nft3wJ594JO56D\n1HVDvdP+q69Umc0Jl4Oxn0UCLaW0Rz7pfylt7l54aQl8+mPwj4M7N/FJ0L1U4crDF4+nrtHC2oN5\n3T6iyWzhx+/sZWtqMU9cNZklE7oeIdJbs2J8aTBb2JNRavtNMYth7FKIvxJGtZ+dWV3fxKNrDjMu\n0INb53Y9V3Mk8HV3IjHcm/omC9OjfAZ1/IoQQgghhL3J32SEfW1+CoqOwyVPqbEeHS15FPxiYfU9\nUNuLYGM4OvYFNNXBpJX2ed6Ey1X2LmtH3+6vKYHPfgYvLIKyLLjiBRXkB07kYHY5kb6uLIj1J9rP\njQ/2ZHf5GF3X+c1HB/n6SD6PXjqBK6aE9fEDWTcjahRGg2b7CBRQ2c3r34eVL3e69PS3yeSW1/Hn\nK+N7HHUyEiwep87+2iuTLIQQQggxVEb+38zE8FFwDDY+AZOuUlk6axxc4MoXoLoAvvjF4O6vK0Un\nwGJjSWdbhz4Er3AIO8c++xh3Yd9KaS0W2PMG/Hs67H5FZY/vS4KEH6ggDTiYU058qBeaprFiWhg7\nT5aQWVxj9XFfHsrj/d3Z3Ld4DKvm2D9T6OHsQHyol+1NgrqxP6uMl7ekc+054UyLHGWH3Q29SxNC\niPR1HZFNjoQQQggh2pIGQcI+LBZVtunkDhc83v3akCmw4FdqnMW4i9R4i6FyfC28cw1EzoUrn1fl\nv7aoKYHU72iYcRePfXqE6vrOwerV08M4tzfZqbaltBc8btvMzpoSePsHkL0TImbBsicgKL7dktLq\nBnLKarlxViQAV0wJ5Ymvj/Phnmx+en5su7WVdY08+ulhJgR78pPzxtq+916aFe3LS5vTqGlowtWx\nb38MbU0t4o7XdxPg4cSvLoyz8w6HTpSfGxt+sWiotyGEEEII0W+S2RT2kfSSKv+84HFw9+95/dyf\nQeh0VfZZkTvw+7PG3AhfPwIeIXBqHzw7B45Y6aBrzZFPwNLEVpcFvL4tg62pRWxPK279WnvoFA9+\nfBCLRe/dnlpKabN32rZ+z+tq7WXPwM1rOwWaoLKaAJNCVSfZEG8XZsf48tHe7E77e/LrZAoq6/nz\nlZMwDWBJ6qwYXxrNOknpfSul/uxALqte3kWQlzMf3jUbb1dHO+9QCCGEEEL0lwSbov/Ks+Hb30P0\nIki4xrZ7jCa44nkwN8An94Ley6DMHna/CsUn4JK/wx0bVeOZ/90In/4EGqyXmLY69CH4juXzAn+8\nXR3Y/KvFbPn16a/Hr5xEamE13x7N792eWkppD9tYSnv0UwhOhCnXt5bMdtQSbMaHnB5bsmJqGFkl\ntexKLzm9Lruc17elc8O5kSSGD2wX1OmRPph6e26z2cubT3LfO3tJCPfi/TtnEeJ9hozREUIIIYQ4\nw0iwKfpH1+Hzn6uxJpc81WXAY5XfGFj6R0j9Dva/O3B7tKauHL5/XJXPxl4IvjFwy9cw5341MuSF\nBVBw1Pq9FacgfTN6/JVsSS1mdowvRkP7z33xpGDCR7nw3IZU9N4E0k4eMGaJbV1pK3IhJwnGX9rt\nssO55USMcsXL1aH1tQvjg3BzNPJhc6Mgs0XnodUH8XV34hcXjrN9v33k5mQiIdy7V+c2LRadx9ce\n5Q+fHWHphEDeuPVcyWgKIYQQQgxjEmyK/jn+BSSvhUUPdhpJYZPpt0LQZNj4VzA32X9/Xdn8NNQU\nq2C3JUA2OcL5v4cfrlbB6OuXWy/xPbIa0MkOXUZueR1zxvh1WmIyGrhtXjR7MsvY1dtS0YmXQ2Uu\nZO/qft2xz9X38cu7XXYwp7y1hLaFq6OJZZOC+eJgHrUNZt7Yls6B7HIeuWQCns4O1h9kZ7OifTmY\nU05VvW2/7o+vPcrzG9K4YWYEz1w/DWcH4wDvUAghhBBC9IcEm2c7XYd9b0Pq+t53ZG2shS9/o2Y5\nzryrb++vaTD/F1CSBoc/6tszeqs8G7Y/A5OuhtCpna9HL4QbV0NDFbxzbeeS2syHKegAACAASURB\nVIMfQNAkvi9WpaZzrQSbAFdNC2eUmyPPbUjt3f5im0tpD7zX/bqja9QYGf/YLpeU1TSQVVJLfIdg\nE2DFtDCq6pt4fVs6T3ydzLyxflw6Obh3e+2HWTG+mC16u1LerjSaLby7M4tLJgfzx8viO2WShRBC\nCCHE8CPB5tnu2Gew+i5443J4aiJ8/TDkHbLt3i3/hLIMuOivYOxHNizuEgiYoMam9FQ6ag/rHlNB\n9nmPdL0mcAKseBFO7YdP7j59prTkpCpdjV/J5pQiwnxciBjlavURLo5GVs2OYt2xAo7lVdi+P2dP\n1aF3/7tQW2Z9TU0JpG/psYT2UI56346ZTYBzokYR5uPC42uP0WC28Njl8Wi9KYPup6kRPjgaDWy3\noZR2X1YZlfVNXDwpeFD3KIQQQggh+k6CzbNZYy18+aAK9Fa+ohrNbH8WnpujOrMe+F/X95ZmwOa/\nw8QrIHpB//ZhMMC8B6DoOBz9pH/P6knuPhXEzbwLvCO6XzvuIljyKBz+GDb+Tb3WnH01T7iCranF\nzB3j123w88NZkbg6Gnl+Q1rv9jnzTmishr1vWL9+fC3o5h6DzdbmQKGena4ZDBpXTlWjXu5bNIZI\nX7fe7bGfXByNJIZ729QkaMPxQowGjdldZJGFEEIIIcTwI8Hm2Wzz01CeqTKT8VfCde/CA8lqVqNm\ngI9uU9lLa756UK1Z+ph99jLxCvAdO7DZTV1XmVsXH5j3M9vumfMTSLhWzQQ98gkc/BDCz+VgtReV\ndU1Wz2u25e3qyDUzIlizP5fs0h463LYVnKCaF+14wfpZ1qOfgle4+geCbhzKKSd8lEuXjXRunTOa\nh5aN544FMbbvzY5mxvhyKKecspqGbtdtPFHIlHBvvFwG5zypEEIIIYToPwk2z1YlJ2HzU6pcc/S8\n06+7+cI5t8Ft61QA+M0jsOGv7UeTpHynym/nPQBeYfbZj8EI838O+YdUw6GBkPwlpG+Chb8B585l\npVZpGlzyNISdAx/eBgWHIX4lW1KKAJgd49vjI340bzQa8OKmk73b78y71D8GHP+8/ev1lZC6TmU1\neygptdYcqC0vVwdumx+No2lo/ig4f3wgFh2+PJTX5ZriqnoO5pQzP9aG+a1CCCGEEGLYkGDzbPXV\nQ2Awwfl/tH7d6AArXoKE61RW77s/qICzqQHW/gpGRcPs++y7p/iV4DO6c3BrDxWn1DxP//Ew/ebe\n3evgDNe8BW7+Kps78XI2nyhiQrAnvu5OPd4e4u3C8sQQ3tuVRWl19xm8dsZdBN6RqrS5rRPfgLle\nnXXtRnlNI5klNVabAw0X8aGejPZz45N9Vrr+NtucUoSuI8GmEEIIIcQII8Hm2ejENypbtuAX4BXa\n9TqDES77D0y/RZ3P/PI3qotr8Qm48P/A1HOg1StGkypvPbUPUr6133PNTfDhrdBYA1e92rdmRu4B\ncPMXcMOH1Dr6sjujlLljbT8/eOeCGGobzby2Ld329zQY4dw7IXMb5Ow5/fqxz8DVDyJmdnv7oVx1\nXrO7zOZQ0zSN5QkhbD9ZTH5FndU1G5IL8XF1GNafQwghhBBCdCbB5tmmqV5lJn3HwMy7e15vMMDF\nf1drdzwL3z4KsRdB7NKB2d/ka9RZRHtmN7//M2RsUZ8jIK7vz/GJhJjF7EovocFs6fG8ZluxgR4s\njgvgze2Z6L35XFNuAEcP2PGc+u/GOkj+CuIuVsFoN1qbA4UM7yBteWIIug6fHTjV6ZrForMxuYi5\nY/1l3IkQQgghxAgjwebZZvszUJIKF/UiM6lpcMGf1TxMN3+48M8Dtz+TI8y9H7J3wskN/X/eiW9g\n05Mw5UZIvLb/zwO2pBThaDQwI8qnV/ctGR9IUVU9GcW9aBTk7AlTrodDH6lS4JMb1PzP8ct7vPVg\nTjlhPi74uFlvDjRcxPi7MzHEkzX7O5fSHs2roKiqngVSQiuEEEIIMeJIsHk2KU6FDX9TZ/3GLOnd\nvZoGix+GB46r85oDacqN4BEM6//cc3bT3KjONJ7c2LmLbXk2fHQ7BEyEZX+z2/Y2pxQxNdIbV0dT\nr+6bGukNwJ7M0t694Tm3g6UJkl6Co2vAyRNGz+/xtkM9NAcaTpYnhLA/q4z0oup2r29MVo2Y5vei\nZFkIIYQQQgwPEmyeLQ5+AC8sVOciL/hT359jGITfMiYnWPhryNqhRnx0Z+cL8OWv4bVL4el4+OZ3\nUHBUBaEf3ALmBrj6NXBwscvWSqobOJxbwdw+zHscG+CBu5Op98Gmb4xqFpT0Mhz7AmIvUBngbpTX\nNpJRPLybA7V1aUIIAJ92yG5uSC4gLsiDAE/nodiWEEIIIYToBwk2z3T1VbD6btUgxz8O7tgEPlFD\nvaueJd6gOsd++zvVAdeaynxY/7jK0q54CQLjYeu/4JmZ8PQkFaxe+g/wG2u3bW1NVZm23pzXbGE0\naCSGe7M7o6z3bzzzLqgphtoSNfKkB4dzhn9zoLZCvF04J2oUa/bntp5pra5vYndGKQvGSQmtEEII\nIcRIJMHmmSx3Lzw/H/a/A/N/CTevVU1uRgKjCc7/A5SkqYyeNd8+qkaAXPRXmLQSrv+fKvO96K/g\nHQFz7lev29GWlCI8nE19DuKmRvpwPK+Cqvqm3t0YNU8F0yZnm0qgD46wYBPg0sQQThRUcSyvEoBt\nqcU0mnUWjJVgUwghhBBiJJJg80y19d/w4vnQVAc3fQaLH1IB3Egy9nwYvQA2/B/UdsgGZu6A/W/D\nrHtVmWkLd3849w649Ws4//d239LmlCJmRftiMvbtfzpTI7yx6HAgq5fZTU2Dy5+FlS+Do1uPyw/m\nlBPqPfybA7W1LD4Io0Frnbm5IbkQV0cj03rZiEkIIYQQQgwPEmyeqSpPwbgL4c7NEDVnqHfTN5oG\nSx+D2lI157OFxQxf/Bw8Q2H+zwdtO5nFNWSV1PZqvmZHU8JV4NTrc5sAwZPVyJMeWCw6B7JHTnOg\nFr7uTswb68enzaW0G08UMivaFydT9yNehBBCCCHE8CTB5plqye/h6jfAddRQ76R/gidDwrWw/Tko\nzVCv7X4V8g6oQNSGLJ+9bE7p+3nNFl6uDowJcGdPZh/ObdqgvsnMfe/uJbOkhkVxI6/8dHlCCDll\ntXy8N4eM4hrmy8gTIYQQQogRa4TVVQqbDVLJrNmi89cvj1FQWd/p2uK4gNYuo/2y+GE4/BGs+6M6\nj7nuj+oM48Qr+v/sXtieVkygpxPRfv0LcKdGePPNkXx0XUfTNDvtDirqGrn99SS2p5Xwm4viuHp6\nuN2ePViWTgzCyXSQxz4/CiDzNYUQQgghRjAJNkW/fHc0n+c3phHi5dzuHGNFXSPfHslnwTh/PJ0d\n+vcmXqHqbOamJ6AyD+oq1NxMOwZqttidUcr0qFH9DhCnRvjwv6RsThZVE+3vbpe95VfUcdPLO0kp\nqOKpHyRwxZQwuzx3sLk7mThvfABfHMwjYpQrUf0M7IUQQgghxNCRYFP0y6tb0wnxcmbjLxe1CzYP\n5ZRzyb8289b2TO5aGNPNE2w05yeqfDZ9E8y8BwLG9/+ZvZBbVktOWS23zRvd72dNjWw5t1lml2Az\npaCKm17eSVlNAy+vmjHiS0+XJ4TwxcE8yWoKIYQQQoxwcmZT9NnxvEq2phZz46yoTt1Z40O9mDfW\nj5e3nKSu0dz/N3P2hGV/hfCZsPBX/X9eLyVlqIY+06P6fwZ2jL87Hs6mvjUJ6mB3Rikrn9tKfZOZ\nd2+fNeIDTYBFcQFcMSWU686NGOqtCCGEEEKIfpBgU/TZq1vTcTIZuGaG9bOBdy6IobCyno/35tjn\nDeNXwK1fgfPgd1lNSi/BzdFIXJBHv59lMGgkhnuzJ6N/wea3R/K5/sXteLs48OFds5kUNrK6z3bF\nyWTkqR8kMj7Yc6i3IoQQQggh+kGCTdEnZTUNfLw3myumhHY5y3F2jC/xoZ78d2MaZos+yDu0r6T0\nUqZE+PR5vmZH0yJ9OJ5fSWVdY5/uf3dnJre/kcS4QA8+uGs2kb5ytlEIIYQQQgwvEmyKPnlvVxZ1\njRZumh3V5RpN07hzQQxpRdV8cyRv8DZnZ5V1jRzLq2B6lI/dnjk1wgddh/1Z5b26T9d1/vHtCX79\n0UHmjfXn7dtm4ufuZLd9CSGEEEIIYS8SbIpeazJbeH1bBjOjR/VY6nhRfDCRvq48uyENXR/a7Obq\nvTks//dmcstqe3Xf3swyLDpMj7TfzNLECG80jV6d22wyW3jw40M89W0yK6aG8eJN03Fzkh5fQggh\nhBBieJJgU/Tat0cLyCmrZdXsnjuzGg0at82LZn9WGdvTSgZhd9bpus4z36dwILucG17aQXFV57mg\nXUlKL8GgqQDRXjydHRgb4N6rYPPpb0/wzs5M7lkUwxNXTcbBTiW9QgghhBBCDAT526rotVe3niTU\n24Ul4wNsWr9yWhh+7o48tyF1gHfWtUM5FSTnV3HVtDBySmu56ZWdNp+XTMooZUKIJ+52ziJOjfBR\nWVMbz7OuP17AzOhR/OKCuH7P+hRCCCGEEGKgSbApeuVYXgXb00q4cVakzc1ynB2M3DxnNBuSCzmS\nWzHAO7Tuwz3ZOJoMPHzxBJ69YSrHTlXyo9eSehzL0mi2sDezzK4ltC2mRvhQXttIWlF1j2trG8wc\ny6tkWqT9zo0KIYQQQggxkCTYFL3y2tZ0nB26HnfSlRvOjcTN0cjzGwc/u9nQZOGTfTmcPyEQL1cH\nFscF8uTVCexML+Het/fQaLZ0ee/RUxXUNprt2hyoxdRIVZZrSyntodxyzBadxHAJNoUQQgghxMgg\nwaawWWl1Ax/vzeGKKaF4u1ofd9IVL1cHrjs3gs8OnKKgsm6AdmjdumMFlNY0snJqWOtrlyWG8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WJsepeThWzcFxag6OU/NwrJqD49Q8emusto2IYW1VcrLZS0iaFRFjy26HrZvj1Dwcq+bgODUH\nx6l5OFbNwXFqHq0eK3ejNTMzMzMzs4ZzsmlmZmZmZmYN52Sz9/hx2Q2wdnGcmodj1Rwcp+bgODUP\nx6o5OE7No6Vj5Xs2zczMzMzMrOF8ZdPMzMzMzMwazsmmmZmZmZmZNZyTzSYmaYSk/5D0oqSVkuZJ\nuljSxmW3rZVI2lTSiZJukDRH0nJJiyXdJ+mvJdU8ziSNl3SrpNfzOn+QdJqkvt29D61M0rGSIk8n\n1qlzqKSZOa5LJD0oaUp3t7UVSfpwPrZezue5FyXdLukvatT1MVUCSX8p6VeS5ufPfa6k6yTtV6e+\n49RFJE2WdImkeyW9mc9rV7SxTofj4XPi+9OROEnaQdI5ku6U9LykVZJekXSTpEltvM8USQ/lGC3O\nMTu0a/aqd+rMMVW1/k8L3zG2r1Onr6TT87G3PB+Lt0oa37g9KY/v2WxSkkYD9wObAzcBjwP7AJOA\nJ4D9I2JheS1sHZK+CPwIeAm4C3gO2AL4JDAUmAEcHYWDTdIRuXwFcA3wOnAYsBNwfUQc3Z370Kok\nbQM8CvQFBgMnRcRPq+qcAlwCLCTFahUwGRgBXBQRZ3Vro1uIpH8FzgbmA78kDYo9DNgb+HVEfLVQ\n18dUCSRdAHyVdHzcSIrR9sDhQD/g+Ii4olDfcepCkmYDY4AlpONmZ+DKiDi2Tv0Ox8PnxPevI3GS\nNB04BngMuI8Uo51Ix1hf4CsR8YMa610InJm3fz0wAPg0sAlwakRc2vg96306ekxVrXsYcHNedzCw\nQ0TMqaoj4FrSMfQEcAspRscAg4CjIuKmhu1QGSLCUxNOwO1AkE4YxfLv5fLLym5jq0zAQaQ/zn2q\nyrckJZ5BOllUyocAC4CVwNhC+SDSDwgBfLrs/ertEyDg18DTwHfz535iVZ2RpC9hC4GRhfKNgTl5\nnf3K3pfeOAEn5c93GjCgxvL+hX/7mConRlsCa4CXgc2rlk3Kn/tcx6lbYzIJ2CGf3w7Mn+kVdep2\nOB4+J5YSpxOAPWuUTyQl+iuBraqWjc/bnANsXBW/hTmGIxu1P7156kisqtYbls+N04GZeb3ta9T7\nTF72G2BQoXxcju0CYMOyP4f3M7kbbRPKVzUPBuYB/1a1+BvAUuA4SRt0Rs7eggAADZtJREFUc9Na\nUkTcGRG3RMTaqvKXgcvyywMLiyaTTkLTI2JWof4K4Nz88ktd12LLvkz6oeCvSMdMLZ8HBgKXRsS8\nSmFELAK+nV9+sQvb2JIkDQS+Rfqx5uSIWFVdJyLeLrz0MVWObUm34zwYEQuKCyLiLuAtUlwqHKcu\nFhF3RcRTkb+ttqEz8fA5sQE6EqeImBYRj9Qov5uUxAwgJZdFlRh8K8emss480vfGgaS/fdaGDh5T\nRZXhTv62jXqVY+zcfOxV3vd3pJ4Dw0jHatNystmcKn30f1UjwXmL9OvI+sAHu7th9h6VL8SrC2UH\n5fltNerfAywDxucv3NYFJO0CfAeYGhH3rKPqumL1y6o61jgfJf2B/TmwNt8TeI6kr9S5D9DHVDme\nIl1Z2UfSZsUFkiYAG5J6D1Q4Tj1LZ+Lhc2LPUus7BjhOpZJ0AnAk8IVYxy1tkgaRfihYBtxbo0qv\niJWTzea0U54/WWf5U3m+Yze0xeqQ1A84Pr8snvDrxi8iVgPPkO51GtWlDWxROS7/Rbpq9g9tVF9X\nrF4iXREdIWn9hjbSxuX5CuAR4BekHwcuBu6XdLek4hUzH1MliIjXgXNI96g/JunHkv5F0rXAr4D/\nAb5QWMVx6lk6Ew+fE3sISdsCHyYlKvcUyjcAtgaW5JhU83fELpTjMpXU1batey1Hk+67nZuPuWq9\nIlZONpvT0DxfXGd5pXyjbmiL1fcdYDfg1oi4vVDu+JXr68CewAkRsbyNuu2N1dA6y61zNs/zs0n3\nshxAukq2OymJmQBcV6jvY6okEXEx6WFo/Uj32f4dcDTwPDCtqnut49SzdCYePif2APlq85Wk7rDn\nF7vK4uOsNEqjD/yM9ECgL7djlZaIlZNNsy4g6cukp8A9DhxXcnMsk7Qv6WrmRRHxQNntsboqf5tW\nA4dHxH0RsSQiHgU+QXoi4MR6Q2tY95H0VdKTLqeRfqXfgPS04LnAlfmJwmbWIHlImv8C9ifd03dh\nuS2ygtNJD246qeoHgJbmZLM5tfXLYaX8jW5oi1XJj4WfSnpM+aTc1azI8StB7j77n6TuX+e1c7X2\nxqrer5LWOZX/+48UH0ICEBHLSE/jhjTcE/iYKoWkA4ELgJsj4oyImBsRyyLiYdKPAi8AZ0qqdMN0\nnHqWzsTD58QS5UTzClLvgWuBY2s8uMbHWQkk7Uh6sN3lEXFrO1driVg52WxOT+R5vT7cO+R5vXs6\nrYtIOo00/tgfSYnmyzWq1Y1fToi2I13RmdtV7WxRg0mf+S7AisIgy0F6ijPAT3LZxfn1umK1Fekq\nzvycAFnjVD73en9gK78Yr1dV38dU96oMDn9X9YJ8TDxE+p6xZy52nHqWzsTD58SSSOoPXE0aK/Mq\n4LO17vOLiKWkH3oG55hU83fErrEr+Sm/xe8X+TvGxFznqVx2ZH79NGn4qFH5mKvWK2LlZLM5Vf6w\nH5z7h79D0oakrhXLgN92d8NamaRzgO8Ds0mJ5oI6Ve/M80NqLJtAepLw/RGxsvGtbGkrgX+vM1Ue\nK39ffl3pYruuWH28qo41zh2kezV3rT7HZbvl+TN57mOqHJWnlA6rs7xSXhm6xnHqWToTD58TSyBp\nAOk+9aNJPXSOi4g161jFcep+86j/HaNy4eG6/HoevDPM0P2kY+2AGtvsHbEqe6BPT52bSN3IAji1\nqvx7ufyystvYShOpW2YAs4BN2qg7BHgVD2zeYybg/Py5n1hVvh0ewLysmNyUP9/Tq8oPBtaSrm4O\nzWU+psqJ0afyZ/sysHXVso/nOC0HNnWcSonPgaxjAPrOxMPnxFLiNBD471znp0CfdmxzfK4/B9i4\nUD4yx25FMX6eGhOrdaw3M6+3fY1ln8nLfgMMKpSPy8fmAmBI2fv+fiblHbImI2k06Y/B5qQvZf8H\n7Esag/NJYHysY2wfaxxJU0gPx1hD6kJb616VeRExrbDOkaSHaqwApgOvA4eTHit/PfCp8MHZbSSd\nT+pKe1JE/LRq2anAD0h/oK8hXaWZDIwgPWjorO5tbWuQNIJ0jtuGdKXzEdIX3SN590vwjEJ9H1Pd\nLF91vh34CPAWcAMp8dyF1MVWwGkRMbWwjuPUhfLnW+mityXwMVI32MoYfq8Vz1mdiYfPie9fR+Ik\n6XLgBOA14Iek81+1mRExs+o9LgLOID1Q7XpgAHAMsCnpQsWljduj3qujx1SdbcwkdaXdISLmVC0T\n6f7byaSHSt5CitExpB9+joq2h1Dp2crOdj11fiJ9CbsceIl0sn+WNA7dxmW3rZUm3r0qtq5pZo31\n9gduJV2hWQ48SnqSWd+y96nVJupc2SwsPwy4m/SFeinwO2BK2e3u7ROpG+Yl+dy2ivRl6wZgnzr1\nfUx1f4z6A6eRbtt4k3SP3wLS2KgHO07dHo+2/h7Na0Q8fE7svjjx7lWxdU3n13mfE3JsluZY3Q0c\nWvb+N9PUmWOqxjYqMXzPlc28vF8+5h7Nx+CifEyOL3v/GzH5yqaZmZmZmZk1nB8QZGZmZmZmZg3n\nZNPMzMzMzMwazsmmmZmZmZmZNZyTTTMzMzMzM2s4J5tmZmZmZmbWcE42zczMzMzMrOGcbJqZmZmZ\nmVnDOdk0MzOrQdJMSR6M2szMrJOcbJqZWa8mKTo4nVB2mxtB0jxJ88puh5mZta5+ZTfAzMysi/1j\njbLTgKHAVOCNqmWz8/x4YP0ubJeZmVmvpgj3EDIzs9aSr/htC2wXEfPKbU3XqFzVjIiR5bbEzMxa\nlbvRmpmZ1VDrnk1JB+autudLGivpNkmLJS2SNEPSNrneKEnTJb0qabmkuySNqfM+60v6e0mzJS2V\ntETSA5I+U6OuJE2RdH/e9gpJz0u6XdIxxTaSkultq7oIT6va3s6SpuVtrJL0iqSrJO1U472n5W2M\nknSGpMfz+8+X9H1JQ2qss7ukq3OX3pW5zQ9LulhS/w6Ew8zMmpCvbJqZWctpz5VNSTOBiRGhQtmB\nwF3ArcBBwN3AH4E/Bw4GngSOAO4DHgcezO/zSeA1YFRELClsbyPgTmBP4GHgftIPwR8DRgPfiohz\nC/W/Dfw98AzwS2AxsBUwDng8IiZLGgmcQOoqDHBxYbdmR8SNeVuHAD8H+gO3AHOAEbmtK4FJEfFw\n4b2nAVOAm4EJwLWkLsgfA8YAvwc+FBErcv3d8/5HXucZYAiwPTAJ2KT4WZiZWe/jZNPMzFpOA5JN\ngGMj4srCsn8HPg8sAi6KiG8Vlp0HfBM4LSKmFsqnkRK4cyLiXwvlg4AbSQnsXhExO5cvBJYDO0bE\nsqr2bhYRr1XtY81utJI2BuYCa4AJEfFYYdluwG+BJyNirxptXQjsHRHP5vI+wHWkJPXrEfFPufwi\n4AzgyIi4qcb7L46ItdVtMzOz3sPdaM3MzDruvmKimf0szxcD36la9p95vkelQNKmwLHArGKiCZCv\nDp4DCPhs1bbeJiWJVK3zWnXZOhwPbAR8o5ho5u38EfgJsKekXWusO7WSaOb6a4GzgbWkZLva8hpt\nXeRE08ys9/PTaM3MzDpuVo2yF/N8dkRUJ4Mv5PmIQtk4oC8Qks6vsb3KPY27FMquBE4FHpN0Lakb\n7wMRsbgDbQfYL8/H1HnvHQvv/VjVsrurK0fEXEnPAyMlbRQRbwDXAF8BbpR0PfBr4DcR8XQH22pm\nZk3KyaaZmVn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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fa3503b7400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tf.reset_default_graph()\n",
    "keras.backend.clear_session()\n",
    "\n",
    "# reshape input to be [samples, time steps, features]\n",
    "X_train = X_train.reshape(X_train.shape[0], X_train.shape[1],1)\n",
    "X_test = X_test.reshape(X_test.shape[0], X_train.shape[1], 1)\n",
    "\n",
    "# create and fit the GRU Model\n",
    "model = Sequential()\n",
    "model.add(GRU(units=4, input_shape=(X_train.shape[1], X_train.shape[2])))\n",
    "model.add(Dense(1))\n",
    "model.compile(loss='mean_squared_error', optimizer='adam')\n",
    "model.summary()\n",
    "model.fit(X_train, Y_train, epochs=20, batch_size=1)\n",
    "\n",
    "# make predictions\n",
    "y_train_pred = model.predict(X_train)\n",
    "y_test_pred = model.predict(X_test)\n",
    "# invert predictions\n",
    "y_train_pred = scaler.inverse_transform(y_train_pred)\n",
    "y_test_pred = scaler.inverse_transform(y_test_pred)\n",
    "\n",
    "#invert originals\n",
    "y_train_orig = scaler.inverse_transform(Y_train)\n",
    "y_test_orig = scaler.inverse_transform(Y_test)\n",
    "\n",
    "# calculate root mean squared error\n",
    "trainScore = k_sqrt(k_mse(y_train_orig[:,0],\n",
    "                          y_train_pred[:,0])\n",
    "                   ).eval(session=K.get_session())\n",
    "print('Train Score: {0:.2f} RMSE'.format(trainScore))\n",
    "testScore = k_sqrt(k_mse(y_test_orig[:,0],\n",
    "                         y_test_pred[:,0])\n",
    "                  ).eval(session=K.get_session())\n",
    "print('Test Score: {0:.2f} RMSE'.format(testScore))\n",
    "\n",
    "# shift train predictions for plotting\n",
    "trainPredictPlot = np.empty_like(normalized_dataset)\n",
    "trainPredictPlot[:, :] = np.nan\n",
    "trainPredictPlot[n_x:len(y_train_pred)+n_x, :] = y_train_pred\n",
    "\n",
    "# shift test predictions for plotting\n",
    "testPredictPlot = np.empty_like(normalized_dataset)\n",
    "testPredictPlot[:, :] = np.nan\n",
    "testPredictPlot[len(y_train_pred)+(n_x*2):len(normalized_dataset), :] = y_test_pred\n",
    "\n",
    "# plot baseline and predictions\n",
    "plt.plot(scaler.inverse_transform(normalized_dataset),label='Original Data')\n",
    "plt.plot(trainPredictPlot,label='y_train_pred')\n",
    "plt.plot(testPredictPlot,label='y_test_pred')\n",
    "plt.legend()\n",
    "plt.xlabel('Timesteps')\n",
    "plt.ylabel('Total Passengers')\n",
    "plt.show()"
   ]
  }
 ],
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